eCite Digital Repository

Predictive Waste Classification Using Field-Based and Environmental Geometallurgy Indicators, Mount Lyell, Tasmania


Parbhakar-Fox, A and Lottermoser, B, Predictive Waste Classification Using Field-Based and Environmental Geometallurgy Indicators, Mount Lyell, Tasmania, Environmental Indicators in Metal Mining, Springer International Publishing, B Lottermoser (ed), Switzerland, pp. 157-177. ISBN 978-3-319-42729-4 (2017) [Research Book Chapter]

Copyright Statement

Copyright 2017 Springer International Publishing Switzerland

DOI: doi:10.1007/978-3-319-42731-7_9


Best practice for acid rock drainage (ARD) risk assessment predominately relies on the geochemical properties of sulfidic rocks. Consequently, a plethora of geochemical tests are routinely utilised by the mining industry to predict ARD formation. Due to limitations associated with these tests and their relatively high costs, analysis of recommended best practice sample numbers is rarely achieved, thus reducing the accuracy of waste management plans. This research aimed to address this through identifying potential geometallurgy indicators using drill core samples (n = 70) obtained from the Comstock Chert, a new prospect proximal to Mount Lyell, western Tasmania, Australia. Samples were subjected to a range of mineralogical analyses, routine ARD geochemical tests (i.e., paste pH; acid-base accounting, ABA; net acid generation, NAG), field-based techniques (e.g., portable X-ray fluorescence, pXRF; short-wave infrared spectrometry, SWIR) and geometallurgical analyses (i.e., HyLogger, Equolip). This study demonstrated: (1) HyLogger data allows identification of acid-neutralizing carbonate minerals; (2) Equolip hardne s data provide a con ervalive indication of lag-time to acid formation; (3) CARD risk grading accurately identifies high and low risk ARD domain; and (4) pXRF data provides a sound indication of the abundance of environmentally significant elements. Consequently, the application of geometallurgical techniques to drill core allows the prediction of ARD characteristics that inform waste characterization and management plans.

Item Details

Item Type:Research Book Chapter
Keywords:acid mine drainage, mine waste management, sulfide oxidation, mining
Research Division:Earth Sciences
Research Group:Geology
Research Field:Geology not elsewhere classified
Objective Division:Environmental Management
Objective Group:Terrestrial systems and management
Objective Field:Evaluation, allocation, and impacts of land use
UTAS Author:Parbhakar-Fox, A (Dr Anita Parbhakar-Fox)
UTAS Author:Lottermoser, B (Professor Bernd Lottermoser)
ID Code:112022
Year Published:2017
Deposited By:CODES ARC
Deposited On:2016-10-21
Last Modified:2018-04-23

Repository Staff Only: item control page